Machines such as, for example, dozers, motor graders, wheel loaders, wheel tractor scrapers, and other types of heavy equipment are used to perform a variety of tasks. The completion of some of these tasks require operation on or near inclines that, if inappropriately traversed by a machine, have the potential to roll the machine over, resulting in equipment damage and possible injury to the operator. When under the direct control of a human operator, the likelihood of rollover may be estimated by the operator and appropriate avoidance measures manually implemented. However, in some situations, rollover may be difficult for the operator to anticipate and, without suitable automated safety measures in place, rollover may be unavoidable. This rollover potential may be even greater when the machine is remotely, autonomously, or semi-autonomously controlled.
Remotely controlled, autonomously controlled, and semi-autonomously controlled machines are capable of operating with little or no human input by relying on information received from various machine systems. For example, based on machine movement input, terrain input, and/or machine operational input, a machine can be controlled to remotely and/or automatically complete a programmed task. By receiving appropriate feedback from each of the different machine systems during performance of the task, continuous adjustments to machine operation can be made that help to ensure precision and safety in completion of the task. In order to do so, however, the information provided by the different machine systems should be accurate and reliable.
An exemplary system that may be used to control a machine is disclosed in U.S. Pat. No. 6,622,091 to Perlmutter et al. that issued on Sep. 16, 2003 (“the '091 patent”). The system of the '091 patent is capable of determining an inclination of a machine. Specifically, the system combines outputs from various sensors, including accelerometers, via a Kalman filter to generate corrected navigation data (including corrected pitch data) of a machine. Using the corrected navigation data from the Kalman filter, the system computes updated navigation data related to a machine.
Although the system of the '091 patent may be useful in determining navigational data for a machine, the system may not provide accurate inclination (e.g., pitch) data due to unexpected non-gravitational accelerations of the machine. For example, acceleration caused by other means such as machine movement or vibration may cause errors in the data obtained by the accelerometers. Further, non-gravitational acceleration may cause the Kalman filter in the '091 patent to incorrectly compensate when generating the corrected pitch data.
The inclination detection system of the present disclosure is directed toward solving one or more of the problems set forth above and/or other problems of the prior art.